کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
553804 | 873538 | 2010 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
New approach for the sequential pattern mining of high-dimensional sequence databases
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
سیستم های اطلاعاتی
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چکیده انگلیسی
In this paper a new algorithm, the Top-Down mining of Sequential patterns (TD-Seq), for mining sequential patterns from high-dimensional stock sequence databases is presented. Existing algorithms are limited by efficiency problems in dealing with high-dimensional sequence databases. To address this problem, a two-phase mining method is proposed, in which a top-down transposition-based searching strategy as well as a new support counting method are exploited. Three pruning rules were also developed to reduce the search space further. Experiments conducted on actual databases demonstrate the improved performance of TD-Seq over existing algorithms.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Decision Support Systems - Volume 50, Issue 1, December 2010, Pages 270–280
Journal: Decision Support Systems - Volume 50, Issue 1, December 2010, Pages 270–280
نویسندگان
Hongyan Liu, Fangzhou Lin, Jun He, Yunjue Cai,